On-Line Visualization of Underground Structures using Context Features
CHEN, Jiazhou
Visualization and manipulation of complex data on wireless mobile devices [IPARLA ]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
State Key Lab CAD&CG [HangZhou]
Visualization and manipulation of complex data on wireless mobile devices [IPARLA ]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
State Key Lab CAD&CG [HangZhou]
GRANIER, Xavier
Visualization and manipulation of complex data on wireless mobile devices [IPARLA ]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
State Key Lab CAD&CG [HangZhou]
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Visualization and manipulation of complex data on wireless mobile devices [IPARLA ]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
State Key Lab CAD&CG [HangZhou]
CHEN, Jiazhou
Visualization and manipulation of complex data on wireless mobile devices [IPARLA ]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
State Key Lab CAD&CG [HangZhou]
Visualization and manipulation of complex data on wireless mobile devices [IPARLA ]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
State Key Lab CAD&CG [HangZhou]
GRANIER, Xavier
Visualization and manipulation of complex data on wireless mobile devices [IPARLA ]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
State Key Lab CAD&CG [HangZhou]
< Réduire
Visualization and manipulation of complex data on wireless mobile devices [IPARLA ]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]
State Key Lab CAD&CG [HangZhou]
Langue
en
Communication dans un congrès
Ce document a été publié dans
ACM Symposium on Virtual Reality Software and Technology (VRST), 2010-11-22, Hong Kong. 2010-11-22p. 167-170
Résumé en anglais
We introduce an on-line framework for the visualizing of underground structures that improves X-Ray vision and Focus and Context Rendering for Augmented Reality. Our approach does not require an accurate reconstruction of ...Lire la suite >
We introduce an on-line framework for the visualizing of underground structures that improves X-Ray vision and Focus and Context Rendering for Augmented Reality. Our approach does not require an accurate reconstruction of the 3D environment and runs on-line on modern hardwares. For these purposes, we extract characteristic features from video frames and create visual cues to reveal occlusion relationships. To enhance the perception of occluding order, the extracted features are either directly rendered, or used to create hybrid blending masks: we thus ensures that the resulting cues are clearly noticeable.< Réduire
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